README.md

EDASH

This repo is still under development and will be refactored in the future.

• continuous.py:

The implementation of information metric for numerical data.

• em_example.ipynb :

The example showcase of applying EM-Algorithm for imputation and information metrics calculation.

• em_runtime_visual.ipynb :

The code for experimenting with the running time and R^2 of EM and KNN method.

• utils.py :

The implemntation of EM-Algorithm imputation and Simulating missing values.

• entropy.ipynb :

Testing whether information metric works fine.

• knn_simulate.ipynb :

The implementation of KNN and testing. Packages are used.

• Todo

For the convenience of testing and implementation, we seperate the process of imputation and information metric.

The module of imputation and information metric will be rearranged.